Computational Advertising: The Hidden Practice Witnessed Every Day

Do you know what advertisers do with your data? Most consumers don’t. Professor Jisu Huh aims to close the knowledge gap and empower consumers with the ability to choose what happens to their data.

For many, computational advertising is a practice that we witness each time we open our internet browser without ever really being made aware of its presence. It’s a force that makes its effects known while simultaneously hiding its inner workings.

For Raymond O. Mithun Endowed Chair in Advertising and Professor Jisu Huh, computational advertising is an exciting new research field with a great deal of opportunities and concerns in connection to the machinations hiding just beneath the surface of our favorite websites.

Seeing the Invisible
Today’s consumers are exposed to an increasing number of hyper-personalized ads created and served by the computational advertising mechanism. If you have ever searched for something online, you likely have received results specifically tied to your interests and previous queries. In the same vein, almost any online shopping you do can affect the ads that pop up across your browser, enticing you to buy similar products. Computational advertising uses machine-learning algorithms based on the analysis of prior consumer behavior to curate a tailored advertising environment for every online shopper. 

For Huh, computational advertising is a fascinating research area with many emerging questions about its hidden inner workings as well as its effects on individual consumers and the whole society.

Huh’s research on computational advertising involves interdisciplinary collaborations with computer scientists. Roughly 10 years ago, researchers at the Carlson School of Management, Department of Computer Science and Engineering, and many other related disciplines around the University of Minnesota created the Social Media and Business Analytics Collaborative (SOBACO). This multidisciplinary research community focuses on research problems stemming from emerging social media and big data research. When Huh was invited to join, she met computer scientists with whom a fruitful research collaboration has generated a number of journal publications and conference papers over the years. 

The work that Huh did with SOBACO pushed her to continue her interdisciplinary research, leading to the formation of her own lab. Today, Huh proudly continues to operate the Minnesota Computational Advertising Laboratory (MCAL). This space is dedicated to studying emerging phenomena and problems in broader communication fields through the lens of computational social science. 

Finding the Right Balance
Through her work, either in the lab or the classroom, one thing has always been clear to Huh: advertising is most effective when it achieves a balance between an advertiser’s strategic goals and a consumer’s informational needs.

With this in mind, Huh focuses her research on helping all parties involved in the advertising ecosystem, where different groups may have different goals. The main goal of her research is “to help the advertising industry and advertisers to develop socially responsible and ethical advertising practices, and also inform and empower consumers.” In her view, the act of empowering consumers by equipping them with knowledge about the inner workings of computational advertising is just as important as helping advertisers craft the right strategies to market their products.

In Huh’s experience, consumers are often unaware of where their data goes when they browse online. This knowledge gap creates friction between advertisers and their potential customers and can foster mistrust in consumers. A potential solution may lie in pushing advertisers and tech companies to be more transparent and allowing consumers to learn what advertisers do with their data.

The Tools for Consumer Empowerment
Despite growing concerns about a lack of transparency, to Huh, all hope for trust between advertisers and consumers is not lost. Tools that already exist can provide consumers with heightened awareness of where their data goes and can help rebuild consumer confidence in the computational advertising ecosystem. 

For example, on many websites that you use each day, you are prompted to accept or reject cookies. The simple existence of this little pop-up has provided remarkable education to the average Internet user on data privacy. These small notifications have sparked numerous conversations regarding the collection and use of consumer data by retailers and advertisers.

Other methods of making the invisible visible also exist. Chances are, you are made aware of sponsored social media content through disclaimers on particular posts. Laws that require such disclosures assist in making consumers knowledgeable of precisely when and where they are becoming the target of advertising. 

Keeping an Eye Ahead
For now, Huh is cautiously optimistic about the future of computational advertising. As Huh continues developing this research area, she works closely with her graduate students and encourages them to take on the role of lead author in their own research.

Huh is particularly excited about the work being done by her current cohort of graduate students. Her students are studying a wide variety of topics, ranging from virtual influencers to social media influencer pay discrepancies and related inequity and diversity issues. Some students are even investigating the future of advertising in the age of AI search engines. 

In addition to her research and teaching at the U, Huh eagerly continues her work as Editor-in-Chief for the Journal of Advertising. Huh believes that “academic researchers, like myself, have an important role to play to set the vision for… the larger advertising field.” In particular, the vision that she is helping to shape features ethically-motivated advertisers and educated consumers.

By Regan Carter

Jisu Huh